The present disclosure relates to methods of processing amplitude-modulated analog signals and associated pickoff signal processing systems and sensors. These methods may, for example, find use in conjunction with sensors that comprise a vibrating structure gyroscope, such as a Coriolis-type gyroscope, and that can be used as an annular rate sensor. These methods may be particularly applicable to MEMS sensors as they are capable of being implemented within standard ASIC processes.
Vibrating structure gyroscopes and other sensors may be fabricated using micro-electro-mechanical-systems (MEMS) technology from a semiconductor e.g. silicon substrate. MEMS manufacturing processes are often used to make small mechanical structures at low cost (relative to traditional manufacturing methods). There is considerable interest in utilizing MEMS gyroscopes in a range of guidance, navigation and platform stabilization applications due to their low cost, small size and inherently robust nature. MEMS gyroscopes operate using a mechanical structure excited and controlled by electronic systems. These sensing structures generally vibrate at a carrier frequency Fc in the order of 14 KHz and have useful information contained within side bands extending from a DC component at 0 Hz to a few hundred Hz either side of the carrier frequency. As MEMS structures are generally very small, the signals of interest are also generally very small, and low noise circuitry and signal processing is required to recover the information with sufficient fidelity.
Some examples of vibrating structure gyroscopes may be found in GB 2322196, U.S. Pat. No. 5,932,804 and U.S. Pat. No. 6,282,958. FIG. 1 shows an example of a prior art vibrating structure gyroscope comprising an annular resonator mounted by flexible support beams extending from an inner periphery of the annular resonator to a boss provided by a semiconductor substrate. The flexible support beams allow the annular resonator to vibrate in response to drive signals provided by drive transducers in a substantially undamped oscillation mode and permit the annular resonator to move in response to an annular velocity applied about an axis normal to its plane. The annular resonator is typically excited into a cos 2θ resonance mode. For a perfectly symmetrical resonator, this mode actually exists as a degenerate pair of primary and secondary vibration modes at a mutual angle of 45 degrees. The primary mode is excited as the carrier mode by the drive signal. When the annular resonator is rotated about an axis normal to its plane, the Coriolis effect causes a secondary vibration in an orthogonal direction that pulls energy into the secondary mode. The amplitude of motion of the secondary mode is proportional to the applied annular velocity and measured by a pickoff signal.
In such a Coriolis-type gyroscope, a quadrature bias may arise due to an imperfect matching of the primary and secondary frequencies in the cos 2θ vibration mode pair. The magnitude of the quadrature bias is proportional to ΔF·sin 4α, where ΔF is the mode frequency split and a is the mode angular alignment with respect to the primary drive axis. The quadrature bias represents a significant error which appears as a large carrier frequency but at 90 degrees phase (phase quadrature) to the expected mechanical vibration. This quadrature bias signal can be several orders of magnitude larger than the pickoff signals of real interest. A processing system for the pick off signals must have a large dynamic range, good linearity and very good phase accuracy to enable an accurate discrimination of the in-phase and quadrature components.
For a vibrating structure gyroscope, the resultant pickoff signal can be considered as an amplitude-modulated analog signal. A processing system must provide for accurate reconstruction of the amplitude and phase of the modulation from DC to the bandwidth of interest (a few hundred Hz). The processing system must also have the ability to reject the large carrier component which has a quadrature phase relationship to the signal of interest, including a quadrature DC component. A low noise, wide dynamic range but accurate phase sensitive detector is therefore required.
In the prior art, accurately phased electronics can enable the quadrature signal to be substantially rejected. However, practical limitations on the accuracy of an analog phase sensitive detector mean that some of the quadrature signal will typically remain and contaminate the true in-phase signal representing the angular rate. WO 2011/144899 provides an example of a typical rate sensor architecture of the type seen in FIG. 2. An analog pickoff signal is input to the annular rate channel including a synchronous detector. The synchronous detector outputs an offset relative to the amplitude of the pickoff signal which is then filtered and converted into a single-ended offset on the rate output signal and input to an analog-to-digital convertor (ADC). The ADC then outputs a digital signal representative of the movement of the annular rate sensor. US 2008/121054 provides another example of annular rate channel output circuitry wherein an analog pickoff signal is amplified and filtered before being converted into a DC voltage by a phase sensitive detector (PSD). The DC voltage is buffered by an amplifier and then converted into digital format by an analog-to-digital convertor (ADC).
FIG. 3 provides an overview of a simple synchronous detector (also known as a synchronous demodulator) which is used in such analog systems to extract the amplitude modulation information from the analog pickoff signal at a carrier frequency Fc. It can be seen that a simple pair of +/−1 square wave reference signals controlled by a clock running at the carrier frequency Fc is used to split the pickoff signal into in-phase and quadrature phase components. The in-phase signal is passed through a low pass filter (LPF) so as to reduce its bandwidth before being passed to a downstream ADC for digitization. Such a system can achieve the required phase accuracy but has the disadvantage that odd harmonic distortion of a signal and noise at odd harmonic frequencies are accepted by the demodulator, which degrades the performance of the processing system. FIG. 4a illustrates the noise considerations that must be taken into account, FIG. 4b shows the odd harmonics introduced by a simple +/−1 synchronous demodulator, and FIG. 4c shows how the information carried by the pickoff signal is transformed to base bands by such a +/−1 demodulation. These limitations are generally acceptable for low performance systems but become a dominant source of error when high performance is required.
The quadrature error arising due to inherent fabrication imperfections is a major challenge in the development of accurate MEMS sensors such as gyroscopes. In order to provide the necessary signal conditioning to implement the complex compensation algorithms required to produce a high performance system, a digital (e.g. software-based) implementation is generally preferred. Most high performance sensor systems therefore need to use a digital implementation and this generally requires the inherently analog sensor output to be digitized first. This is typically achieved by using an unsynchronized analog-to-digital convertor (ADC) which directly digitizes the amplitude-modulated carrier signal generated by a pickoff transducer. A problem with direct digitization of the pickoff signal is that a very high speed ADC is required and this limits the dynamic range available (number of bits), and that large and complex processing is needed in order to accurately extract the amplitude modulation information while simultaneously resolving the phase information sufficiently to reject the large quadrature component. While this can provide a route to high performance if implemented in discrete component form, it makes it difficult and costly to integrate using a general purpose ASIC (application-specific integrated circuit) process. ASIC technology is usually used for its compatibility with small and cheap MEMS sensors.
There remains a need for improved signal processing systems and methods for sensors such as a MEMS sensor, especially a vibrating structure gyroscope, that do not suffer from the issues outlined above.